Dr. Mojtaba Ahmadiehkhanesar | Robotics | Best Researcher Award

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Mojtaba Ahmadiehkhanesar | Robotics | Best Researcher Award

University of Nottingham | United Kingdom

Dr. Mojtaba Ahmadieh Khanesar (PhD, MIET’20, SMIEEE’16, MASME’23) is a distinguished research fellow in optical metrology and machine learning at the Department of Mechanical, Materials, and Manufacturing Engineering, University of Nottingham, UK. With extensive international experience in Denmark, Turkey, Iran, and the UK, his research spans metrology, robotics, control systems, AI, and machine learning. He earned his Ph.D. in Control Engineering from K. N. Toosi University of Technology, Tehran, Iran, with a thesis on model reference interval type-2 fuzzy control of SISO nonlinear systems, following an M.Sc. on sliding mode fuzzy control of a rotary inverted pendulum and a B.Sc. in Control Engineering. Dr. Khanesar possesses strong technical expertise in MATLAB, Python, OpenCV, AVR, ARM, Arduino, and robotics platforms including UR5, Baxter, and Sawyer, as well as metrology tools such as laser trackers, laser interferometers, Sensofar, Zygo, and Polytec systems. He has contributed significantly to EPSRC-funded projects including Robodome, HARISOM, and Chattyfactories, supervising PhD and undergraduate students while developing high-accuracy robotic systems and virtual instruments. He also serves as associate editor for Human-Centric Intelligent Systems, Complex and Intelligent Systems, and Energies, contributing to special issues on robust control and electromechanical systems. Dr. Khanesar’s research output includes 110 documents cited 2,363 times, with an h-index of 25, reflecting his significant impact in the field. He has received multiple honors including the Collaborate to Innovate Award, top student awards, and top paper recognitions in IEEE and Robotics journals, and he maintains active memberships in IEEE, ASME, IET, and BCS, demonstrating leadership and influence in engineering and computational intelligence communities worldwide.

Profile : Scopus | ORCID | Google Scholar

Featured Publications

  • Khanesar, M. A., Kayacan, E., Teshnehlab, M., & Kaynak, O. (2011). Extended Kalman filter based learning algorithm for type-2 fuzzy logic systems and its experimental evaluation. IEEE Transactions on Industrial Electronics, 59(11), 4443–4455.

  • Khanesar, M. A., Kayacan, O., Yin, S., & Gao, H. (2015). Adaptive indirect fuzzy sliding mode controller for networked control systems subject to time-varying network-induced time delay. IEEE Transactions on Fuzzy Systems, 23(1), 205–214.

  • Sharafi, Y., Khanesar, M. A., & Teshnehlab, M. (2013). Discrete binary cat swarm optimization algorithm. In Proceedings of the 3rd IEEE International Conference on Computer, Control and Communication (pp. xx–xx). IEEE.

  • Kayacan, E., Kayacan, E., & Khanesar, M. A. (2015). Identification of nonlinear dynamic systems using type-2 fuzzy neural networks—A novel learning algorithm and a comparative study. IEEE Transactions on Industrial Electronics, 62(3), 1716–1724.

  • Camci, E., Kripalani, D. R., Ma, L., Kayacan, E., & Khanesar, M. A. (2018). An aerial robot for rice farm quality inspection with type-2 fuzzy neural networks tuned by particle swarm optimization-sliding mode control hybrid algorithm. Swarm and Evolutionary Computation, 41, 1–8.

 

Liang Li | Robot System | Best Researcher Award

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Dr. Liang Li | Robot System | Best Researcher Award

Academic Leader of the Key Laboratory | Baoji University of Arts and Sciences | China

Dr. Li Liang is an academic scholar affiliated with the Baoji University of Arts and Sciences in Baoji, China. He has contributed to the fields of mechanical engineering, composite materials, robotics, and intelligent manufacturing through a consistent body of research. His publications demonstrate expertise in process modeling, knowledge graph construction, and optimization techniques for robotic systems. With an active research profile indexed in Scopus, Li Liang has achieved recognition with multiple works cited internationally. His academic career reflects a dedication to advancing modern manufacturing technologies and their integration with artificial intelligence methods in industrial applications.

Publication Profile

Scopus

Education Background

Dr. Li Liang pursued his higher education in engineering disciplines, developing a strong foundation in mechanical sciences and computational techniques. His academic training emphasized advanced mechanics, material science, and intelligent control systems, which enabled him to engage with cross-disciplinary research in automation and industrial technologies. Through rigorous study and research training, he cultivated proficiency in analytical methods and modern computational tools. His education was centered on building both theoretical and practical expertise, allowing him to contribute effectively to innovative solutions in machining processes, robotic trajectory optimization, and composite structural analysis across applied engineering fields.

Professional Experience

As an Associate faculty member at Baoji University of Arts and Sciences, Dr. Li Liang has actively participated in teaching, research, and collaborative projects. His professional experience spans guiding students, publishing scholarly works, and engaging in joint research efforts with national and international colleagues. He has authored and co-authored numerous papers, focusing on numerical modeling, intelligent robotics, and advanced materials. His contributions also extend to integrating artificial intelligence approaches with traditional engineering processes. In addition, he has built professional collaborations with more than thirty co-authors, reflecting his ability to work in team-driven scientific environments that promote applied industrial innovations.

Awards and Honors

While specific awards and grants are not publicly listed, Dr. Li Liang has earned academic recognition through consistent citations of his research and scholarly contributions. His studies published in reputable open-access journals such as Electronics and Processes have contributed to the international research community, further solidifying his academic standing. The impact of his work, reflected in increasing citations and collaborations, signifies recognition of his scholarly achievements. His commitment to advancing research on machining knowledge graphs, composite mechanics, and robotic arm optimization highlights his academic merit and serves as a foundation for future honors and acknowledgments.

Research Focus

Dr. Li Liang’s primary research interests lie in mechanical engineering, intelligent manufacturing, composite materials, and robotics. His recent works have explored the construction of machining process knowledge graphs for route recommendations, numerical analysis of advanced braided composites, and reinforcement learning optimization for robotic grasping. These areas collectively showcase his interdisciplinary focus, combining computational intelligence with mechanical design. By addressing challenges in trajectory planning, process optimization, and structural performance, his research contributes to advancing both theoretical insights and industrial applications. His focus is on creating smart, adaptive systems that bridge materials science, artificial intelligence, and industrial engineering.

Publication Top Notes

  • Construction of a Machining Process Knowledge Graph and Its Application in Process Route Recommendation
    Published Year: 2025
    Citation: 1

  • Numerical Analysis on Mechanical Properties of 3D Five-Directional Circular Braided Composites
    Published Year: 2025
    Citation: 1

  • Improved PPO Optimization for Robotic Arm Grasping Trajectory Planning and Real-Robot Migration
    Published Year: Not listed
    Citation: 1

Conclusion

Through his academic journey, Dr. Li Liang has built a strong reputation as a researcher contributing to intelligent manufacturing and computational engineering. His publications demonstrate expertise across multiple technical domains, and his collaborative work highlights his adaptability and scholarly engagement. With a growing number of citations and impactful studies, his career reflects both innovation and academic integrity. His dedication to teaching and research at Baoji University of Arts and Sciences ensures that his contributions will continue to influence the development of advanced robotic systems, material analysis, and smart manufacturing processes in both academic and applied industrial contexts.

Assoc. Prof. Dr. Samuel Moveh | Robotics | Best Researcher Award

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Assoc. Prof. Dr. Samuel Moveh | Robotics | Best Researcher Award

Associate Professor, Transporta un sakaru instituts TSI, Latvia

Dr. Samuel Moveh is a passionate researcher and academician dedicated to advancing knowledge in mechanical engineering, artificial intelligence, and robotics. With a strong background in teaching and research, he has contributed significantly to academia through his innovative work in autonomous systems, intelligent control, and smart technologies. Dr. Moveh has held key academic positions across multiple universities, including his role as a Visiting Associate Professor at the Transport and Telecommunication Institute, Latvia, and a University Professor at Istanbul Gelisim University, Türkiye. His commitment to mentorship and scholarly excellence is evident in his numerous publications, research collaborations, and contributions to technological advancements.

Publication Profile

🎓 Education

Dr. Samuel Moveh holds a Ph.D. in Mechanical Engineering from Universiti Teknologi Malaysia (UTM) 🏛️, where he specialized in autonomous systems and intelligent control. He earned his Master’s degree in Mechanical Production Engineering from Ahmadu Bello University, Nigeria, and a Bachelor’s degree in Mechanical Engineering (Honors) from Modibbo Adama University, Nigeria. His academic journey is marked by excellence, with a strong focus on applied mechanics, fluid dynamics, and robotics.

💼 Experience

With over a decade of academic and research experience, Dr. Moveh has contributed to various institutions globally. As a Visiting Associate Professor at the Transport and Telecommunication Institute, Latvia, he taught advanced courses in aeronautical systems, artificial intelligence, and robotics. He also served as a University Professor and Erasmus Coordinator at Istanbul Gelisim University, where he played a pivotal role in international academic collaborations. His research experience spans across National University of Singapore, where he worked on smart facade technologies, and Infinity FM, Malaysia, contributing to smart city development. His earlier roles include lecturing positions at Modibbo Adama University, Nigeria, where he mentored numerous students in mechanical engineering and intelligent systems.

🏅 Awards and Honors

Dr. Moveh has been recognized for his outstanding contributions to engineering and academia. He has received multiple awards for his research excellence, particularly in autonomous vehicle control, intelligent systems, and sustainable smart technologies. His contributions to interdisciplinary research and technological innovations have earned him a reputation as a leading scholar in his field.

🔬 Research Focus

Dr. Moveh’s research interests lie in autonomous vehicle control, artificial intelligence, robotics, and smart city technologies. He has made significant contributions to developing intelligent lane-keeping systems, smart facade technologies, and machine learning applications in engineering. His work focuses on integrating AI-driven control systems into real-world applications, ensuring sustainability, efficiency, and innovation in mechanical and smart technologies.

📚 Publications

A review of some pure-pursuit based path tracking techniques for control of autonomous vehicles – International Journal of Computer Applications (2016) 📖 Cited by 229

Lane keeping maneuvers using proportional integral derivative (PID) and model predictive control (MPC) – Journal of Robotics and Control (2021) 🤖 Cited by 28

Development of edge-based lane detection algorithm using image processing – JOIV: International Journal on Informatics Visualization (2018) 🖥️ Cited by 23

Housing quality standard and Covid-19 pandemic: A call for attention in Nigeria – Journal of Science, Engineering, Technology and Management (2020) 🏠 Cited by 22

Non-intrusive room occupancy prediction performance analysis using different machine learning techniques – Energies (2022) 🔥 Cited by 20

IoT and big data technologies: opportunities and challenges for higher learning – International Journal of Recent Technology and Engineering (2020) 📡 Cited by 18

AI Driven Thermal People Counting for Smart Window Facade Using Portable Low‐Cost Miniature Thermal Imaging Sensors – Preprints (2020) 🌡️ Cited by 17

Evaluating the performance of fuzzy-PID control for lane recognition and lane-keeping in vehicle simulations – Electronics (2023) 🚗 Cited by 13

The influence of silicon carbide particulate loading on tensile, compressive and impact strengths of Al-Sicp composite for sustainable development – Chemical Engineering Transactions (2018) ⚙️ Cited by 10

🔚 Conclusion

Dr. Samuel Moveh is a distinguished researcher whose work bridges the gap between mechanical engineering, artificial intelligence, and robotics. His extensive contributions to smart technologies, autonomous systems, and intelligent control systems have made a lasting impact in academia and industry. With a strong commitment to innovation, mentorship, and research excellence, he continues to inspire the next generation of engineers and scientists worldwide. 🚀

Paolo Mercorelli | Robotics | Women Researcher Award

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Prof Dr. Paolo Mercorelli | Robotics | Women Researcher Award

Professor, Leuphana University of Lueneburg, Germany

🎓 Paolo Mercorelli is a distinguished Professor and Chair of Control and Drive Systems at Leuphana University of Lueneburg, Germany. With a PhD in Systems Engineering from the University of Bologna, Italy, he has made significant contributions to control systems and robotics. His international teaching and research roles, coupled with numerous awards, underscore his influence in the field.

Publication Profile

Strengths for the Award

  • Extensive Research Experience: Paolo Mercorelli has a robust academic and research background with significant contributions across multiple prestigious institutions worldwide, including the University of California, Santa Barbara, Ostfalia University, and Leuphana University. His research spans various cutting-edge fields, such as robotics, control systems, and Kalman filters, demonstrating a broad and deep expertise that aligns with the criteria for high-impact research awards.
  • Recognition and Awards: Mercorelli’s research has been consistently recognized at an international level, with multiple best paper awards at significant conferences, highlighting the quality and impact of his work. His inclusion in the top 2% of scientists by Elsevier and Stanford University’s metrics further solidifies his standing as a leading researcher in his field.
  • Leadership and Influence: Serving as Editor-in-Chief for journals like “Transactions on Computer Research” and “Mathematics,” Mercorelli has not only contributed through his research but also shaped the direction of research in engineering mathematics and computer research. This leadership role underlines his influence in the academic community.
  • Global Academic Involvement: His role as a visiting professor at various international universities, such as Lodz University of Technology and Chandigarh University, indicates his global influence and commitment to disseminating knowledge, which is crucial for awards recognizing research leadership.

Areas for Improvement

  • Specific Focus on Women’s Research: While Mercorelli’s achievements are exceptional, the Research for Women Researcher Award typically emphasizes contributions that advance women’s roles in research or address gender-specific challenges in academia. Mercorelli’s CV does not explicitly mention efforts or research focused on promoting women in science or addressing gender disparities in research. This could be a limitation if the award criteria emphasize these aspects.
  • Involvement in Gender-Inclusive Initiatives: Active participation or leadership in initiatives aimed at fostering gender equality in research, mentoring women in STEM, or contributing to women-centric research topics could strengthen his candidacy for this specific award.

 

Education

🎓 Paolo Mercorelli earned his PhD in Systems Engineering from the University of Bologna, Italy, in 1998. His academic journey also includes a one-year research stint at the University of California, Santa Barbara, USA, which laid the foundation for his future endeavors in control systems.

Experience

💼 Paolo Mercorelli has a rich professional background, starting as a Postdoctoral Researcher at Asea Brown Boveri Corporate Research, Heidelberg, Germany, where he secured three patents. He served as a Senior Researcher and leader of the control group at the Institute of Automation and Informatics, Germany. Later, he became an Associate Professor at Ostfalia University of Applied Sciences and is currently a Full Professor at Leuphana University of Lueneburg. Additionally, he has held visiting professorships at Lodz University of Technology, Poland, and Chandigarh University, India.

Research Focus

🔍 Paolo Mercorelli specializes in control systems with a focus on applications of Kalman filters, robotics, wavelets, geometric control, and sliding mode control. His research integrates advanced mathematical techniques to enhance the efficiency and precision of robotic and control systems.

Awards and Honors

🏆 Paolo Mercorelli has been recognized with several prestigious awards, including the Marie Curie Actions Research Fellowship and seven best international conference paper awards. His exceptional contributions have placed him on the list of the top 2% scientists by Elsevier and Stanford University from 2019 to 2023. He is also the Editor-in-Chief of two leading journals.

Publication Top Notes

📚 Paolo Mercorelli has authored numerous high-impact publications. His work is frequently cited in the field, reflecting his influence in control systems and engineering mathematics. Here are some of his top-cited works:

“Advanced Sliding Mode Control for Automotive Applications” – Published in IEEE Transactions on Industrial Electronics, 2013 Cited by 120 articles

“Wavelet-Based Fault Detection in Induction Motors” – Published in IEEE Transactions on Power Electronics, 2014 Cited by 110 articles

“Kalman Filter Techniques in Robotics” – Published in Robotics and Autonomous Systems, 2017 Cited by 95 articles

“Geometric Control Applications in Robotics” – Published in Control Engineering Practice, 2020 Cited by 85 articles

“Applications of Wavelets in Control Systems” – Published in Automatica, 2023 Cited by 75 articles

Conclusion

While Paolo Mercorelli is undoubtedly a distinguished and highly accomplished researcher with significant contributions to the fields of control systems, robotics, and engineering mathematics, his profile might not fully align with the specific objectives of the Research for Women Researcher Award. The award typically prioritizes candidates who have made substantial contributions to advancing women’s roles in research or who focus on research that benefits women directly. Given his impressive academic and research credentials, he might be more suitable for awards that recognize general excellence in research and leadership rather than those focused specifically on women’s contributions to science and academia.